Abstract
In the chemical industry, planning and scheduling are labor-intensive, complex, rolling processes. Interdependent decisions have to be made around different stages within the supply chain (purchases, production, distribution, exchanges, storage levels, and sales). In taking these decisions the overall enterprise margin needs to be maximized across the global supply chain. To support making these decisions the chemicals supply chain has been modeled using GMOS/NetSim, an AIMMS-based network optimization tool jointly developed by Shell Global Solutions and ORTEC. Years of extensive collaboration with various customers have made GMOS/NetSim a proven tool for strategic supply chain studies. For this project a module was developed to calculate accumulated costs/margins throughout the supply chain. The outcomes are used to do detailed margin analyses. The key challenge was to integrate the model into the monthly S&OP at SCE. Input data needs to be obtained from 15+ people around the world from various fields of expertise on a regular basis, as market conditions constantly change. Moreover, actual data is used for model validation purposes and margin analyses for past months. The key outcomes from the optimization are shared with the user community twice every month. The main benefit of this project is that we are able to establish a unified global base plan and a unified approach for fact-based decision making. The complex mathematical model behind this approach includes a great level of detail reflecting reality in everyday SCE business. This improves both the quality and speed of business decisions at 3 months (S&OP) and multi-year (business plan) horizons across the global supply chain.
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© 2014 Springer International Publishing Switzerland
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van Dongen, T., van den Hurck, D. (2014). Optimization of Sales and Operations Planning at Shell Chemicals Europe. In: Huisman, D., Louwerse, I., Wagelmans, A. (eds) Operations Research Proceedings 2013. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-07001-8_64
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DOI: https://doi.org/10.1007/978-3-319-07001-8_64
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